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Two mechanisms, induced fit (IF) and conformational selection (CS), have been proposed to explain ligand recognition coupled conformational changes. The histidine binding protein (HisJ) adopts the CS mechanism, in which a pre-equilibrium is established between the open and the closed states with the ligand binding to the closed state. Despite being structurally similar to HisJ, the maltose binding protein (MBP) adopts the IF mechanism, in which the ligand binds the open state and induces a transition to the closed state. To understand the molecular determinants of this difference, we performed molecular dynamics (MD) simulations of coarse-grained dual structure based models. We find that intra-protein contacts unique to the closed state are sufficient to promote the conformational transition in HisJ, indicating a CS-like mechanism. In contrast, additional ligand-mimicking contacts are required to “induce” the conformational transition in MBP suggesting an IF-like mechanism. In agreement with experiments, destabilizing modifications to two structural features, the spine helix (SH) and the balancing interface (BI), present in MBP but absent in HisJ, reduce the need for ligand-mimicking contacts indicating that SH and BI act as structural restraints that keep MBP in the open state. We introduce an SH like element into HisJ and observe that this can impede the conformational transition increasing the importance of ligand-mimicking contacts. Similarly, simultaneous mutations to BI and SH in MBP reduce the barrier to conformational transitions significantly and promote a CS-like mechanism. Together, our results show that structural restraints present in the protein structure can determine the mechanism of conformational transitions and even simple models that correctly capture such structural features can predict their positions. MD simulations of such models can thus be used, in conjunction with mutational experiments, to regulate protein ligand interactions, and modulate ligand binding affinities., Graphical abstract Image 1, Highlights • MBP operates by induced fit, HisJ by the conformational selection mechanism. • Dual structure based models (dSBMs) encode two structures of a protein. • MD simulations of dSBMs can identify the mechanism of conformational transitions. • Locks, absent in HisJ, hold MBP open with ligand contacts required for closing. • Binding mechanisms can be modified by altering such structural locks.

Disorders in bile acid transport and metabolism have been related to a number of metabolic disease states, atherosclerosis, type-II diabetes, and cancer. Bile acid-binding proteins (BABPs), a subfamily of intracellular lipid-binding proteins (iLBPs), have a key role in the cellular trafficking and metabolic targeting of bile salts. Within the family of iLBPs, BABPs exhibit unique binding properties including positive binding cooperativity and site-selectivity, which in different tissues and organisms appears to be tailored to the local bile salt pool. Structural and biophysical studies of the past two decades have shed light on the mechanism of bile salt binding at the atomic level, providing us with a mechanistic picture of ligand entry and release, and the communication between the binding sites. In this review, we discuss the emerging view of bile salt recognition in intestinal- and liver-BABPs, with examples from both mammalian and non-mammalian species. The structural and dynamic determinants of the BABP-bile–salt interaction reviewed herein set the basis for the design and development of drug candidates targeting the transcellular traffic of bile salts in enterocytes and hepatocytes.

The main protease (Mpro) of SARS-CoV and SARS-CoV-2 is a key enzyme in viral replication and a promising target for the development of antiviral therapeutics. The understanding of this protein is based on a number of observations derived from earlier x-ray structures, which mostly consider substrates or ligands as the main reason behind modulation of the active site. This lead to the concept of substrate-induced subsite cooperativity as an initial attempt to explain the dual binding specificity of this enzyme in recognizing the cleavage sequences at its N- and C-termini, which are important processing steps in obtaining the mature protease. The presented hypothesis proposes that structural heterogeneity is a property of the enzyme, independent of the presence of a substrate or ligand. Indeed, the analysis of Mpro structures of SARS-CoV and SARS-CoV-2 reveals a conformational diversity for the catalytically competent state in ligand-free structures. Variation in the binding site appears to result from flexibility at residues lining the S1 subpocket and segments incorporating methionine 49 and glutamine 189. The structural evidence introduces “structure-based recognition” as a new paradigm in substrate proteolysis by Mpro. In this concept, the binding space in subpockets of the enzyme varies in a non-cooperative manner, causing distinct conformations, which recognize and process different cleavage sites, as the N- and C-termini. Insights into the recognition basis of the protease provide explanation to the ordered processing of cleavage sites. The hypothesis expands the conformational space of the enzyme and consequently opportunities for drug development and repurposing efforts., Graphical abstract Image 1, Highlights • Structures of SARS-CoV and SARS-CoV-2 Mpro show conformational heterogeneity. • Variations in the active site of Mpro are ligand- and substrate-independent. • Proteolytic recognition in Mpro is based on structural heterogeneity. • Substrate processing takes place by “structure-based recognition”. • The finding expands opportunities for structure-based drug design and repurposing.

Angiotensin converting enzyme 2 (ACE2) plays a key role in renin–angiotensin system regulation and amino acid homeostasis. Human ACE2 acts as the receptor for severe acute respiratory syndrome coronaviruses SARS-CoV and SARS-CoV-2. ACE2 is also widely expressed in epithelial cells of the lungs, heart, kidney, and pancreas. It is considered an important drug target for treating SARS-CoV-2 as well as pulmonary diseases, heart failure, hypertension, renal diseases, and diabetes. Despite the critical importance, the mechanism of ligand binding to the human ACE2 receptor remains unknown. Here, we have addressed this challenge through all-atom simulations using a novel ligand Gaussian accelerated molecular dynamics (LiGaMD) method. Microsecond time scale LiGaMD simulations have unprecedentedly captured multiple times of spontaneous binding and unbinding of a potent inhibitor MLN-4760 in the ACE2 receptor. With ligand far away in the unbound state, the ACE2 receptor samples distinct Open, Partially Open, Closed, and Fully Closed conformations. Upon ligand binding to the active site, conformational ensemble of the ACE2 receptor is biased toward the Closed state as observed in the X-ray experimental structure. The LiGaMD simulations thus suggest a conformational selection mechanism for ligand recognition by the highly flexible ACE2 receptor, which is expected to facilitate rational drug design targeting human ACE2 against coronaviruses and other related human diseases.

Induced fit and conformational selection are two dominant binding mechanisms in biology. Although induced fit has been widely accepted by supramolecular chemists, conformational selection is rarely studied with synthetic systems. In the present research, we report a macrocyclic host whose binding mechanism is unambiguously assigned to conformational selection. The kinetic and thermodynamic aspects of this system are studied in great detail. It reveals that the kinetic equation commonly used for conformational selection is strictly followed here. In addition, two mathematical models are developed to determine the association constants of the same guest to the two host conformations. A “conformational selectivity factor” is defined to quantify the fidelity of conformational selection. Many details about the kinetic and thermodynamic aspects of conformational selection are revealed by this synthetic system. The conclusion and the mathematical models reported here should be helpful in understanding complex molecular recognition in both biological and synthetic systems., Conformational selection is one of the two dominant binding mechanisms in biology, but has rarely been studied in synthetic systems. Here, the authors report a supramolecular system that strictly follows the binding mechanism of conformational selection.

Detoxication, or 'drug-metabolizing', enzymes and drug transporters exhibit remarkable substrate promiscuity and catalytic promiscuity. In contrast to substrate-specific enzymes that participate in defined metabolic pathways, individual detoxication enzymes must cope with substrates of vast structural diversity, including previously unencountered environmental toxins. Presumably, evolution selects for a balance of 'adequate' kcat /KM values for a wide range of substrates, rather than optimizing kcat /KM for any individual substrate. However, the structural, energetic, and metabolic properties that achieve this balance, and hence optimize detoxication, are not well understood. Two features of detoxication enzymes that are frequently cited as contributions to promiscuity include the exploitation of highly reactive versatile cofactors, or cosubstrates, and a high degree of flexibility within the protein structure. This review examines these intuitive mechanisms in detail and clarifies the contributions of the classic ligand binding models 'induced fit' (IF) and 'conformational selection' (CS) to substrate promiscuity. The available literature data for drug metabolizing enzymes and transporters suggest that IF is exploited by these promiscuous detoxication enzymes, as it is with substrate-specific enzymes, but the detoxication enzymes uniquely exploit 'IFs' to retain a wide range of substrates at their active sites. In contrast, whereas CS provides no catalytic advantage to substrate-specific enzymes, promiscuous enzymes may uniquely exploit it to recruit a wide range of substrates. The combination of CS and IF, for recruitment and retention of substrates, can potentially optimize the promiscuity of drug metabolizing enzymes and drug transporters.

Protein dynamics play a critical role in ligand binding, and different models have been proposed to explain the relationships between protein motion and molecular recognition. Here, we present a study of ligand-binding processes associated with large conformational changes of a protein to elucidate the critical choices in ensemble-docking approaches for effective prediction of the binding geometry. Two study cases were selected in which binding involves different protein motions and intermolecular interactions and, accordingly, conformational selection and induced-fit mechanisms play different roles: binding of multiple ligands to the acetylcholine binding protein and highly specific binding of D-allose to the allose binding protein. Our results indicated that the ensemble-docking technique can provide reliable predictions of the structure of ligand-protein complexes, starting from simulations of the apo systems, when suitable methodological choices are made according to the different mechanistic scenarios. In particular, accelerated molecular dynamics simulations are suitable for conformational sampling when the unbound and bound states are separated by high energy barriers, provided that the acceleration parameters are carefully set to extensively sample the relevant conformations. A strategy specifically developed for geometric clustering of the binding site proved to be effective for selecting a set of conformations relevant to binding from the MD trajectory. Specific strategies have to be selected to incorporate different degrees of ligand-induced protein flexibility into the docking or pose-refinement steps.

We review the role conformational ensembles can play in the analysis of biomolecular dynamics, molecular recognition, and allostery. We introduce currently available methods for generating ensembles of biomolecules and illustrate their application with relevant examples from the literature. We show how, for binding, conformational ensembles provide a way of distinguishing the competing models of induced fit and conformational selection. For allostery we review the classic models and show how conformational ensembles can play a role in unravelling the intricate pathways of communication that enable allostery to occur. Finally, we discuss the limitations of conformational ensembles and highlight some potential applications for the future.

Intrinsically disordered proteins (IDPs) are a newly recognized class of functional proteins that rely on a lack of stable structure for function. They are highly prevalent in biology, play fundamental roles, and are extensively involved in human diseases. For signaling and regulation, IDPs often fold into stable structures upon binding to specific targets. The mechanisms of these coupled binding and folding processes are of significant importance because they underlie the organization of regulatory networks that dictate various aspects of cellular decision-making. This review first discusses the challenge in detailed experimental characterization of these heterogeneous and dynamics proteins and the unique and exciting opportunity for physics-based modeling to make crucial contributions, and then summarizes key lessons from recent de novo simulations of the structure and interactions of several regulatory IDPs.

The FtsZ protein is a self-polymerizing GTPase that plays a central role in bacterial cell division. Several C8-substituted GTP analogs are known to inhibit the polymerization of FtsZ by competing for the same binding site as its endogenous activating ligand GTP. Free energy calculations of the relative binding affinities to FtsZ for a set of five C8-substituted GTP analogs were performed. The calculated values agree well with the available experimental data, and the main contribution to the free energy differences is determined to be the conformational restriction of the ligands. The dihedral angle distributions around the glycosidic bond of these compounds in water are known to vary considerably depending on the physicochemical properties of the substituent at C8. However, within the FtsZ protein, this substitution has a negligible influence on the dihedral angle distributions, which fall within the narrow range of −140° to −90° for all investigated compounds. The corresponding ensemble average of the coupling constants 3 J(C4,H1′) is calculated to be 2.95 ± 0.1 Hz. The contribution of the conformational selection of the GTP analogs upon binding was quantified from the corresponding populations. The obtained restraining free energy values follow the same trend as the relative binding affinities to FtsZ, indicating their dominant contribution.

Acylphosphatase is a small enzyme that catalyzes the hydrolysis of acyl phosphates. Here, we present the solution structure of acylphosphatase from Bacillus subtilis (BsAcP), the first from a Gram-positive bacterium. We found that its active site is disordered, whereas it converted to an ordered state upon ligand binding. The structure of BsAcP is sensitive to pH and it has multiple conformations in equilibrium at acidic pH (pH

Background: Serine proteases KLK2 and KLK3 clear the way for spermatozoa before impregnation. Results: Enzymatic assays and structures of KLK2 elucidate its catalytic action, especially when compared with conformations of similar proteases. Conclusion: Flexible loops around the active site of serine proteases open concertedly upon substrate binding. Significance: This mechanistic model will stimulate the design of pharmaceutical inhibitors., Human kallikrein-related peptidase 2 (KLK2) is a tryptic serine protease predominantly expressed in prostatic tissue and secreted into prostatic fluid, a major component of seminal fluid. Most likely it activates and complements chymotryptic KLK3 (prostate-specific antigen) in cleaving seminal clotting proteins, resulting in sperm liquefaction. KLK2 belongs to the “classical” KLKs 1–3, which share an extended 99- or kallikrein loop near their non-primed substrate binding site. Here, we report the 1.9 Å crystal structures of two KLK2-small molecule inhibitor complexes. In both structures discontinuous electron density for the 99-loop indicates that this loop is largely disordered. We provide evidence that the 99-loop is responsible for two biochemical peculiarities of KLK2, i.e. reversible inhibition by micromolar Zn2+ concentrations and permanent inactivation by autocatalytic cleavage. Indeed, several 99-loop mutants of KLK2 displayed an altered susceptibility to Zn2+, which located the Zn2+ binding site at the 99-loop/active site interface. In addition, we identified an autolysis site between residues 95e and 95f in the 99-loop, whose elimination prevented the mature enzyme from limited autolysis and irreversible inactivation. An exhaustive comparison of KLK2 with related structures revealed that in the KLK family the 99-, 148-, and 220-loop exist in open and closed conformations, allowing or preventing substrate access, which extends the concept of conformational selection in trypsin-related proteases. Taken together, our novel biochemical and structural data on KLK2 identify its 99-loop as a key player in activity regulation.

The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads. © 2013 Elsevier B.V.

In the realm of protein-protein interactions, the assembly process of homooligomers plays a fundamental role because the majority of proteins fall into this category. A comprehensive understanding of this multistep process requires the characterization of the driving molecular interactions and the transient intermediate species. The latter are often short-lived and thus remain elusive to most experimental investigations. Molecular simulations provide a unique tool to shed light onto these complex processes complementing experimental data. Here we combine advanced sampling techniques, such as metadynamics and parallel tempering, to characterize the oligomerization landscape of fibritin foldon domain. This system is an evolutionarily optimized trimerization motif that represents an ideal model for experimental and computational mechanistic studies. Our results are fully consistent with previous experimental nuclear magnetic resonance and kinetic data, but they provide a unique insight into fibritin foldon assembly. In particular, our simulations unveil the role of nonspecific interactions and suggest that an interplay between thermodynamic bias toward native structure and residual conformational disorder may provide a kinetic advantage.

A necessary feature of the immune system, TCR (T-cell receptor) cross-reactivity has been implicated in numerous autoimmune pathologies and is an underlying cause of transplant rejection. Early studies of the interactions of alphabeta TCRs (T-cell receptors) with their peptide-MHC ligands suggested that conformational plasticity in the TCR CDR (complementarity determining region) loops is a dominant contributor to T-cell cross-reactivity. Since these initial studies, the database of TCRs whose structures have been solved both bound and free is now large enough to permit general conclusions to be drawn about the extent of TCR plasticity and the types and locations of motion that occur. In the present paper, we review the conformational differences between free and bound TCRs, quantifying the structural changes that occur and discussing their possible roles in specificity and cross-reactivity. We show that, rather than undergoing major structural alterations or 'folding' upon binding, the majority of TCR CDR loops shift by relatively small amounts. The structural changes that do occur are dominated by hinge-bending motions, with loop remodelling usually occurring near loop apexes. As predicted from previous studies, the largest changes are in the hypervariable CDR3alpha and CDR3beta loops, although in some cases the germline-encoded CDR1alpha and CDR2alpha loops shift in magnitudes that approximate those of the CDR3 loops. Intriguingly, the smallest shifts are in the germline-encoded loops of the beta-chain, consistent with recent suggestions that the TCR beta domain may drive ligand recognition.

Current models of receptor activation are based on either of two basic mechanisms: agonist induction or conformational selection. The importance of one pathway relative to the other is controversial. In this article, the impossibility of distinguishing between the two mechanisms under a thermodynamic approach is shown. The effect of receptor mutation on the constants governing ligand–receptor equilibria is discussed. The two-state model of agonism both in its original formulation (one cycle) and including multiple active states (multiple cycles) is used. Pharmacological equations for the double (two cycles) two-state model are derived. The simulations performed suggest that the double two-state model of agonism can be a useful model for assessing quantitatively the changes in pharmacological activity following receptor mutation.